Blood‐based biomarker prescreening in the SKYLINE secondary prevention study with gantenerumab

Abstract

AbstractBackgroundSKYLINE is a new secondary prevention study in Alzheimer's disease (AD) enrolling amyloid‐positive, cognitively normal individuals at risk for clinical AD between 60 and 80 years and treating them with gantenerumab or placebo for 4 years. Based on available data from other studies, we expect only 15% of individuals to be amyloid‐positive in this screening population. We developed a blood‐based biomarker (BBBM) prescreening test to screen out participants who have a low likelihood of amyloid positivity by positron emission tomography (PET) or cerebrospinal fluid (CSF) testing before entering the main screening of SKYLINE.MethodWe explored multiple individual key AD BBBMs (measured with Elecsys® prototype assays) and combinations in three large cohorts (BioFINDER‐1, AIBL, A4) of cognitively unimpaired and subjective cognitive decline/mild cognitive impairment participants. We used predefined thresholds for amyloid PET and/or CSF pTau/Abeta42 as the reference standard for amyloid positivity. The performance of the BBBM was assessed by evaluating the positive and negative predictive value (PPV and NPV) for amyloid positivity, and screen‐out proportions based on a range of potential thresholds. Those metrics were translated into the total number of participants that need to be screened and the reduction of the number of participants that need to be screened with PET or CSF testing to reach the target sample size.ResultWe identified a combination of two key AD biomarkers expected to enable a high NPV at moderate PPV, screening out 40–50% of participants, amongst whom are only 3–5% true amyloid positives (falsely ruled out). This BBBM prescreening would reduce the need for PET or CSF testing by 40% while requiring screening of 8% more participants to compensate for the wrongly excluded amyloid positives.ConclusionThe implementation of Elecsys® blood‐based prescreening in SKYLINE will significantly reduce site and participant burden, accelerate the study enrollment, and save screening costs by reducing unnecessary downstream screening assessments such as cognitive batteries, magnetic resonance imaging, and PET or CSF testing.